O

Oracle

Builds databases, business apps and cloud services

Principal Data Scientist - Supply Chain Operations

Data Science +1Confirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • At least 3 years of experience in data engineering, analytics, automation, artificial intelligence or machine learning, or related technical roles; the education section separately specifies 8 years of experience in data science, machine learning, data engineering, or a related field.
  • Experience designing and developing scalable data pipelines, analytics platforms, and automation solutions.
  • Proven experience delivering data products and dashboards supporting cross-functional business operations.
  • Experience applying predictive analytics or machine learning to solve operational or supply chain challenges.
  • Ability to independently lead complex technical initiatives from concept through implementation.
  • Strong proficiency in SQL and Python for data engineering, automation, and analytics.
  • Experience with ETL/ELT pipelines, data modeling, orchestration frameworks, and cloud-based data platforms.
  • Knowledge of artificial intelligence/machine learning techniques, predictive analytics, and automation frameworks.
  • Experience with business intelligence and visualization tools such as Oracle Analytics Cloud, Tableau, or Power BI.
  • Understanding of forecasting, inventory management, manufacturing operations, logistics, and supply planning concepts.
  • Strong analytical and problem-solving abilities with attention to detail.
  • Ability to explain technical concepts to technical and business audiences.
  • Ability to manage multiple priorities in a fast-paced, rapidly evolving environment.
  • Ability to influence stakeholders and drive technical solutions without direct managerial authority.
  • Self-motivation and interest in automation, continuous improvement, and innovation.
  • A Bachelor's degree or Master's degree in Data Science, Mathematics, Statistics, or Computer Science.

Responsibilities

  • Design, build, and maintain scalable data automation solutions supporting OCI's global supply chain.
  • Develop artificial intelligence and machine learning models to improve forecasting, inventory optimization, supply planning, logistics execution, manufacturing readiness, and operational performance.
  • Identify opportunities to eliminate manual processes through automation, predictive analytics, and intelligent workflows.
  • Build reusable automation frameworks and data products to improve operational efficiency and business scalability.
  • Evaluate emerging artificial intelligence and automation technologies and recommend practical applications across supply chain operations.
  • Design and develop robust data pipelines, models, and architectures supporting real-time operational reporting and advanced analytics.
  • Build scalable datasets enabling forecasting, planning, inventory management, supplier performance, and deployment execution.
  • Ensure data quality, governance, reliability, and accessibility across multiple enterprise systems.
  • Develop dashboards, scorecards, and self-service analytics to improve operational visibility across global supply chain functions.
  • Collaborate with engineering teams to integrate data across Oracle Fusion Cloud Applications, operational systems, and cloud platforms.
  • Develop operational dashboards, key performance indicator frameworks, and control tower capabilities providing end-to-end visibility into supply chain performance.
  • Create intelligent alerting mechanisms to proactively identify operational risks, exceptions, and bottlenecks.
  • Build predictive models supporting scenario planning, capacity management, supplier performance, and deployment readiness.
  • Translate complex operational data into actionable insights supporting day-to-day execution and long-term planning.
  • Partner with Supply Planning, Procurement, Manufacturing, Logistics, Capacity Management, and Data Center Operations teams to understand business challenges and develop scalable technical solutions.
  • Collaborate with product managers, engineers, and business stakeholders to define analytics requirements and deliver data solutions.
  • Provide technical guidance and subject matter expertise for automation initiatives and enterprise data projects.
  • Influence best practices for data engineering, analytics, and automation across the organization.
  • Drive improvements in data quality, automation, reporting accuracy, and operational efficiency.
  • Identify opportunities to simplify processes, reduce technical debt, and improve data platform maintainability.
  • Document technical designs, data models, and automation solutions to support long-term scalability and operational excellence.
  • Stay current on emerging technologies in artificial intelligence, machine learning, cloud computing, and data engineering.

Desired Qualifications

  • Experience supporting supply chain, manufacturing, logistics, procurement, or cloud infrastructure operations.
  • Familiarity with Oracle Fusion Cloud Applications, including Supply Chain Management, Procurement, Planning, or Enterprise Resource Planning.
  • Experience working with cloud technologies and distributed systems architectures.

About the Company

Oracle

Builds databases, business apps and cloud services

Oracle builds databases, business applications, and cloud infrastructure for companies and public-sector organizations. Oracle Database stores and processes business data, while Oracle Cloud Infrastructure provides computing, storage, and networking for applications and AI workloads. Fusion Cloud Applications support finance, human resources, supply chains, and customer service, helping businesses manage everyday operations and reporting. Customers pay for cloud subscriptions and usage, software licenses, support, hardware, and consulting, with deployment options in Oracle's cloud or their own data centers. Oracle was founded in 1977 and is headquartered in Austin, Texas.

Company size
10,001+
Company stage
IPO
Headquarters
Austin, TX
Founded
1977

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